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Dimension reduction in heterogeneous parametric spaces with application to naval engineering shape design problems

Advanced modeling and simulation in engineering sciences, 2018-09, Vol.5 (1), p.25-25, Article 25

2018

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Hull Shape Design Optimization with Parameter Space and Model Reductions, and Self-Learning Mesh Morphing

Journal of marine science and engineering, 2021-02, Vol.9 (2), p.185

2021

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Enhancing CFD predictions in shape design problems by model and parameter space reduction

Advanced modeling and simulation in engineering sciences, 2020-10, Vol.7 (1), p.1-19, Article 40

2020

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A DeepONet multi-fidelity approach for residual learning in reduced order modeling

Advanced modeling and simulation in engineering sciences, 2023-07, Vol.10 (1), p.12-21, Article 12

2023

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A Supervised Learning Approach Involving Active Subspaces for an Efficient Genetic Algorithm in High-Dimensional Optimization Problems

SIAM journal on scientific computing, 2021-01, Vol.43 (3), p.B831-B853

2021

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A non-intrusive approach for the reconstruction of POD modal coefficients through active subspaces

Comptes rendus. Mecanique, 2019-11, Vol.347 (11), p.873-881

2019

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Model Order Reduction: Volume 2: Snapshot-Based Methods and Algorithms

Benner, Peter

1st edition., 2020

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A Local Approach to Parameter Space Reduction for Regression and Classification Tasks

Journal of scientific computing, 2024-06, Vol.99 (3), p.83, Article 83

2024

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Kernel‐based active subspaces with application to computational fluid dynamics parametric problems using the discontinuous Galerkin method

International journal for numerical methods in engineering, 2022-12, Vol.123 (23), p.6000-6027

2022

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A digital twin framework for civil engineering structures

Computer methods in applied mechanics and engineering, 2024-01, Vol.418, p.116584, Article 116584

2024

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A multifidelity approach coupling parameter space reduction and nonintrusive POD with application to structural optimization of passenger ship hulls

International journal for numerical methods in engineering, 2023-03, Vol.124 (5), p.1193-1210

2023

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Multi‐fidelity data fusion through parameter space reduction with applications to automotive engineering

International journal for numerical methods in engineering, 2023-12, Vol.124 (23), p.5293-5311

2023

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Model Order Reduction: Snapshot-Based Methods and Algorithms

2020

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On the comparison of LES data-driven reduced order approaches for hydroacoustic analysis

Computers & fluids, 2021-02, Vol.216, p.104819, Article 104819

2021

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ATHENA: Advanced Techniques for High dimensional parameter spaces to Enhance Numerical Analysis

Software impacts, 2021-11, Vol.10, p.100133, Article 100133

2021

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PyGeM: Python Geometrical Morphing

Software impacts, 2021-02, Vol.7, p.100047, Article 100047

2021

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Multi‐fidelity data fusion for the approximation of scalar functions with low intrinsic dimensionality through active subspaces

Proceedings in applied mathematics and mechanics, 2021-03, Vol.20 (S1), p.n/a

2021

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EZyRB: Easy Reduced Basis method

Journal of open source software, 2018-04, Vol.3 (24), p.661

2018

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PyDMD: Python Dynamic Mode Decomposition

Journal of open source software, 2018-02, Vol.3 (22), p.530

2018

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BladeX: Python Blade Morphing

Journal of open source software, 2019-02, Vol.4 (34), p.1203

2019

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Reduced Order Isogeometric Analysis Approach for PDEs in Parametrized Domains

Quantification of Uncertainty: Improving Efficiency and Technology, 2020, Vol.137, p.153-170

2020

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A Data-Driven Partitioned Approach for the Resolution of Time-Dependent Optimal Control Problems with Dynamic Mode Decomposition

Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2020+1, p.225-238

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Combined Parameter and Model Reduction of Cardiovascular Problems by Means of Active Subspaces and POD-Galerkin Methods

Mathematical and Numerical Modeling of the Cardiovascular System and Applications, 2018, Vol.16, p.185-207

2018

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Basic ideas and tools for projection-based model reduction of parametric partial differential equations

Model Order Reduction, 2020, p.1-47

2020

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Pilot study for the evaluation of safety profile of a potential inhibitor of SARS-CoV-2 endocytosis

Acta bio-medica : Atenei Parmensis, 2020-11, Vol.91 (13-S), p.e2020009

2020

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Dimension reduction in heterogeneous parametric spaces with application to naval engineering shape design problems

Hull Shape Design Optimization with Parameter Space and Model Reductions, and Self-Learning Mesh Morphing

Enhancing CFD predictions in shape design problems by model and parameter space reduction

A DeepONet multi-fidelity approach for residual learning in reduced order modeling

A Supervised Learning Approach Involving Active Subspaces for an Efficient Genetic Algorithm in High-Dimensional Optimization Problems

A non-intrusive approach for the reconstruction of POD modal coefficients through active subspaces

Model Order Reduction: Volume 2: Snapshot-Based Methods and Algorithms

A Local Approach to Parameter Space Reduction for Regression and Classification Tasks

Kernel‐based active subspaces with application to computational fluid dynamics parametric problems using the discontinuous Galerkin method

A digital twin framework for civil engineering structures

A multifidelity approach coupling parameter space reduction and nonintrusive POD with application to structural optimization of passenger ship hulls

Multi‐fidelity data fusion through parameter space reduction with applications to automotive engineering

Model Order Reduction: Snapshot-Based Methods and Algorithms

On the comparison of LES data-driven reduced order approaches for hydroacoustic analysis

ATHENA: Advanced Techniques for High dimensional parameter spaces to Enhance Numerical Analysis

PyGeM: Python Geometrical Morphing

Multi‐fidelity data fusion for the approximation of scalar functions with low intrinsic dimensionality through active subspaces

EZyRB: Easy Reduced Basis method

PyDMD: Python Dynamic Mode Decomposition

BladeX: Python Blade Morphing

Reduced Order Isogeometric Analysis Approach for PDEs in Parametrized Domains

A Data-Driven Partitioned Approach for the Resolution of Time-Dependent Optimal Control Problems with Dynamic Mode Decomposition

Combined Parameter and Model Reduction of Cardiovascular Problems by Means of Active Subspaces and POD-Galerkin Methods

Basic ideas and tools for projection-based model reduction of parametric partial differential equations

Pilot study for the evaluation of safety profile of a potential inhibitor of SARS-CoV-2 endocytosis

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